Drone delivery is an emerging service at the early adoption stage. It is imperative to understand what it takes for the public to accept such emerging services. This study asks what mechanism influences people’s switching intention in e-commerce drone delivery services. A 7 points Likert scale questionnaire were developed after the two rounds of pretest and a total of 83 surveys were collected from a business school in USA. This study applies privacy calculus theory and technology anxiety in innovation to develop a research model. An empirical survey and structural equation modeling analysis with SmartPLS and a consistent PLS algorithm are used to understand the hedging effect of relative advantages of drone delivery services and technology anxiety on the switching intention of e-commerce consumers. Theoretically, this research adds the e-commence literature, suggesting that people appreciate drone delivery’s speed and environmental protection advantages. However, privacy risk severity and vulnerability are not significant predictors of technology anxiety, negatively impacting switching intention. This study also provided practical contribution to improve the service development of e-commerce company to deliver their products to their customers with the most efficient resources being used.

This study provides insights into the initial and post-adoption of cloud computing services by integrating information technology adoption, social influence, trust, security, and information systems quality theories. Social influence, hedonicity, and automaticity are hedonic predictors of user satisfaction with cloud computing services. Perceived risks, trust in the provider, and system quality are utilitarian predictors of user satisfaction with cloud computing services. The Partial Least Squares (PLS) was employed to test eight hypotheses on the causal relationships between the variables. Six out of eight hypotheses were supported. Hedonic factors appear to have more influence than the utilitarian factor of increasing user satisfaction with cloud computing services in the school setting. The findings lead to both theoretical and practical implications for improving the initial and post-adoption of cloud computing services.

Knowledge management has become a major focal point of many scholarly discussions and industry decisions in the recent past. Knowledge arbitrage, concerned with enabling the flow of knowledge from surplus pools of knowledge to deficit ones, is a part of knowledge management and sharing. Strategic knowledge arbitrage and strategic knowledge serendipity (SKARSE) have been conceptualized as a strategic version of knowledge arbitrage, embodying the idea of a better, faster, and more efficient handling of knowledge assets. Despite being a part of academic research and discussions for the past two decades, which has resulted in an evident deepening of the knowledge era, the research on SKARSE has not yet reached a significant level of maturity, mandating additional and more contemporary investigations. Responding to this need, this article sought to motivate research in the area by applying the systematic literature review (SLR) approach to create an organized body of knowledge and set the future research agenda. We executed the SLR using a well-defined search protocol to identify 22 congruent studies, employing thematic analysis to aggregate and evaluate congruent evidence. As a result, we first delineated three main themes—conceptualizations of SKARSE, antecedents of SKARSE, and consequences of SKARSE—carried out a critical appraisal of the findings to identify research gaps and suggest potential research questions, and formulated a conceptual framework embodying varied aspects of SKARSE. This article offers significant implications for theory and practice.